Transcriptome profiling of lentil in response to Ascochyta lentis infection

  1. García-García, Pedro 1
  2. Vaquero, Francisca 1
  3. Vences, F. Javier 1
  4. Sáenz de Miera, Luis E. 1
  5. Polanco, Carlos 1
  6. González, Ana I. 1
  7. Horres, Ralf 2
  8. Krezdorn, Nicolas 2
  9. Rotter, Björn 2
  10. Winter, Peter 2
  11. Pérez de la Vega, Marcelino 1
  1. 1 Universidad de León, Area de Genética, Dpto. de Biología Molecular, 24071 León
  2. 2 GenXPro GmbH, Altenhöferallee 3, 60438, Frankfurt am Main
Revista:
Spanish journal of agricultural research

ISSN: 1695-971X 2171-9292

Año de publicación: 2019

Volumen: 17

Número: 4

Tipo: Artículo

DOI: 10.5424/SJAR/2019174-14982 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Spanish journal of agricultural research

Objetivos de desarrollo sostenible

Resumen

Aim of study: The purpose was to identify some general and genotypic-specific defense responses, in order to obtain a set of candidate genes presumably involved in the resistance.Area of study: The experiment was carried out in León, Spain.Material and methods: We have analyzed the response of three lentil genotypes to Ascochyta lentis (isolate AL 84) at transcriptomic level using the Massive Analysis of cDNA Ends (MACE) technique: the susceptible cultivar 'Lupa', the moderately resistant 'ILL5588' and the resistant wild accession 'BG 16880' (L. culinaris subsp. orientalis).Main results: MACE results yielded a total of 50,935 contigs. The average number of detected contigs in each of the six samples was approximately of 40,000. In response to Ascochyta infection, the jasmonic acid pathway and the lignin biosynthesis were up-regulated in resistant genotypes, while they were down-regulated in the susceptible one. The response to chitin, the salicylic pathway and the auxin response were activated only in the resistant L. c. culinaris genotype, while the giberellin synthesis was only induced in the susceptible L. c. culinaris cv. 'Lupa'. A set of 18 lentil gene sequences putatively involved in the response to the pathogen were validated by RT-qPCR.Research highlights: It can be concluded that in response to the infection by Ascochyta, the lignin biosynthesis and the JA pathway were critical for the resistance, while the giberellin synthesis seems to be related with susceptibility to the pathogen.

Información de financiación

Spanish Ministerio de Econom?a y Competitividad (co-financed with FEDER funds). AGL2013-44714-R. Consejer?a de Educaci?n, Junta de Castilla y Le?n, Spain. LE113G18.

Financiadores

Referencias bibliográficas

  • Abdullah SNA, Akhtar MS, 2016. Plant and necrotrophic fungal pathogen interaction: Mechanism and mode of action. In: Plant, soil and microbes; Hakeem KR, Akhtar MS, Abdullah SNA (eds). pp: 29-53. Springer Int Publ Switzerland. https://doi.org/10.1007/978-3-319-27455-3_3
  • Almeida NF, Krezdorn N, Rotter B, Winter P, Rubiales D, Vaz Patto MC, 2015. Lathyrus sativus transcriptome resistance response to Ascochyta lathyri investigated by deepSuperSAGE analysis. Front Plant Sci 6: 178. https://doi.org/10.3389/fpls.2015.00178
  • Amil-Ruiz F, Blanco-Portales R, Muñoz-Blanco J, Caballero JL, 2011. The strawberry plant defense mechanism: A molecular review. Plant Cell Physiol 52: 1873-1903. https://doi.org/10.1093/pcp/pcr136
  • Anders S, Huber H, 2010. Differential expression analysis for sequence count data. Genome Biol 11: R106. https://doi.org/10.1186/gb-2010-11-10-r106
  • Benjamini Y, Hochberg Y, 1995. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J Roy Stat Soc B 57: 289-300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
  • Burdiak P, Rusaczonek A, Witon D, Glów D, Karpinski S, 2015. Cysteine-rich receptor-like kinase CRK5 as a regulator of growth, development, and ultraviolet radiation responses in Arabidopsis thaliana. J Exp Bot 66: 3325-3337. https://doi.org/10.1093/jxb/erv143
  • Buscaill P, Rivas S, 2014. Transcriptional control of plant defence responses. Curr Opin Plant Biol 20: 35-46. https://doi.org/10.1016/j.pbi.2014.04.004
  • Canonne J, Froidure-Nicolas S, Rivas S, 2011. Phospholipases in action during plant defense signaling. Plant Signal Behav 6: 13-18. https://doi.org/10.4161/psb.6.1.14037
  • Chang S, Puryear J, Cairney J, 1993. A simple and efficient method for isolating RNA from pine trees. Plant Mol Biol Rep 11: 113-116. https://doi.org/10.1007/BF02670468
  • Davidson JA, Kimber RBE, 2007. Integrated disease management of Ascochyta blight in pulse crops. Eur J Plant Pathol 119: 99-110. https://doi.org/10.1007/s10658-007-9132-x
  • Fich EA, Segerson NA, Rose JA, 2016. The plant polyester cutin: Biosynthesis, structure and biological roles. Annu Rev Plant Biol 67: 207-233. https://doi.org/10.1146/annurev-arplant-043015-111929
  • Fondevilla S, Rotter B, Krezdorn N, Jüngling R, Winter P, Rubiales D, 2014. Identification of genes involved in resistance to Didymella pinodes in pea by deepSuperSAGE transcriptome profiling. Plant Mol Biol Rep 32: 258-269. https://doi.org/10.1007/s11105-013-0644-6
  • Fondevilla S, Krezdorn N, Rotter B, Kahl G, Winter P, 2015. In planta identification of putative pathogenicity factors from the chickpea pathogen Ascochyta rabiei by de novo transcriptome sequencing using RNA-Seq and Massive Analysis of cDNA Ends. Front Microbiol 6: 1329. https://doi.org/10.3389/fmicb.2015.01329
  • Fondevilla S, Fernández-Romero MD, Satovic Z, Rubiales D, 2018. Expressional and positional candidate genes for resistance to Peyronellaea pinodes in pea. Euphytica 214: 236. https://doi.org/10.1007/s10681-018-2316-y
  • Ford R, Pang ECK, Taylor PWJ, 1999. Genetics of resistance to ascochyta blight (Ascochyta lentis) of lentil and the identification of closely linked RAPD markers. Theor Appl Genet 98: 93-98. https://doi.org/10.1007/s001220051044
  • Ford R, Tan D, Vaghefi N, Mustafa B, 2017. Abscisic acid activates pathogenesis-related defense gene signaling in lentils. In: Mechanism of plant hormone signaling under stress, 1st edn, Vol. 1; Pandey G (ed). pp: 243-270. John Wiley & Sons. https://doi.org/10.1002/9781118889022.ch10
  • Fu J, Wang S, 2011. Insights into auxin signaling in plant-pathogen interactions. Front Plant Sci 2: 74. https://doi.org/10.3389/fpls.2011.00074
  • Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, et al., 2011. Full-length transcriptome assembly from RNA-seq data without a reference genome. Nat Biotechnol 29: 644-652. https://doi.org/10.1038/nbt.1883
  • Huot B, Yao J, Montgomery BL, He SY, 2014. Growth-defense tradeoffs in plants: A balancing act to optimize fitness. Mol Plant 7: 1267-1287. https://doi.org/10.1093/mp/ssu049
  • Khorramdelazad M, Bar I, Whatmore P, Smetham G, Bhaaskaria V, Yang Y, Bai1 SH, Mantri N, Zhou Y, Ford R, 2018. Transcriptome profiling of lentil (Lens culinaris) through the first 24 hours of Ascochyta lentis infection reveals key defence response genes. BMC Genomics 19: 108. https://doi.org/10.1186/s12864-018-4488-1
  • Kim MC, Panstruga R, Elliott C, Muller J, Devoto A, Yoon HW, Park HC, Cho MJ, Schulze-Lefert P, 2002. Calmodulin interacts with MLO protein to regulate defence against mildew in barley. Nature 416: 447-451. https://doi.org/10.1038/416447a
  • Lu K, Liang S, Wu Z, Bi C, Yu Y, Wang X, Zhang D, 2016. Overexpression of an Arabidopsis cysteine-rich receptor-like protein kinase, CRK5, enhances abscisic acid sensitivity and confers drought tolerance. J Exp Bot 67: 5009-5027. https://doi.org/10.1093/jxb/erw266
  • Madrid E, Rajesh PN, Rubio J, Gil J, Millán T, Chen W, 2012. Characterization and genetic analysis of an EIN4-like sequence (CaETR-1) located in QTLAR1 implicated in ascochyta blight resistance in chickpea. Plant Cell Rep 31: 1033-1042. https://doi.org/10.1007/s00299-011-1221-9
  • Mengiste T, 2012. Plant immunity to necrotrophs. Annu Rev Phytopathol 50: 267-294. https://doi.org/10.1146/annurev-phyto-081211-172955
  • Mustafa BM, Coram TE, Pang ECK, Taylor PWJ, Ford RA, 2009. cDNA microarray approach to decipher lentil (Lens culinaris) responses to Ascochyta lentis. Australas Plant Pathol 38: 617-631. https://doi.org/10.1071/AP09048
  • Navarro L, Bari R, Achard P, Lisón P, Nemri A, Harberd NP, Jones JD, 2008. DELLAs control plant immune responses by modulating the balance of jasmonic acid and salicylic acid signaling. Curr Biol 18: 650-655. https://doi.org/10.1016/j.cub.2008.03.060
  • Ocaña S, Seoane P, Bautista R, Palomino C, Claros GM, Torres AM, Madrid E, 2015. Large-scale transcriptome analysis in faba bean (Vicia faba L.) under Ascochyta fabae infection. PLoS ONE 10: e0135143. https://doi.org/10.1371/journal.pone.0135143
  • Peever TL, 2007. Role of host specificity in the speciation of Ascochyta pathogens of cool season food legumes. Eur J Plant Pathol 119: 119-126. https://doi.org/10.1007/s10658-007-9148-2
  • Pérez de la Vega M, Fratini R, Muehlbauer FJ, 2011. Lentil. In: Genetics, genomics and breeding of cool season grain legumes; Pérez de la Vega M, Torres AM, Cubero JI, Kole C (eds). pp: 98-150. Science Publishers-CRC Press. https://doi.org/10.1201/b11407
  • Roundhill SJ, Fineran BA, Cole ALJ, Ingerfeld M, 1995. Structural aspects of Ascochyta blight of lentil. Can J Bot 73: 485-497. https://doi.org/10.1139/b95-049
  • Ruijter JM, Ramakers C, Hoogaars WMH, Karlen Y, Bakker O, van den Hoff MJB, Moorman AFM, 2009. Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data. Nucleic Acids Res 37: e45. https://doi.org/10.1093/nar/gkp045
  • Sambasivam P, Taylor PWJ, Ford R, 2017. Pathogenic variation and virulence related responses of Ascochyta lentis on lentil. Eur J Plant Pathol 147: 265-277. https://doi.org/10.1007/s10658-016-0999-2
  • Sari E, Bhadauria V, Vandenberg A, Banniza S, 2017. Genotype-dependent interaction of lentil lines with Ascochyta lentis. Front Plant Sci 8: 764. https://doi.org/10.3389/fpls.2017.00764
  • Sari E, Bhadauria V, Ramsay L, Borhan MH, Lichtenzveig J, Bett KE, Vandenberg A, Banniza S, 2018. Defense responses of lentil (Lens culinaris) genotypes carrying non-allelic ascochyta blight resistance genes to Ascochyta lentis infection. PLoS ONE 13: e0204124. https://doi.org/10.1371/journal.pone.0204124
  • Segers G, Bradshaw N, Archer D, Blissett K, Oliver P, 2001. Alcohol oxidase is a novel pathogenicity factor for Cladosporium fulvum, but aldehyde dehydrogenase is dispensable. MPMI 3: 367-377. https://doi.org/10.1094/MPMI.2001.14.3.367
  • Soundarajan S, Jedd G, Li X, Ramos-Pamploña M, Chua NH, Naqvi NI, 2004. Woronin body function in Magnaporthe grisea is essential for efficient pathogenesis and for survival during nitrogen starvation stress. Plant Cell 16: 1564-1574. https://doi.org/10.1105/tpc.020677
  • Sudheesh S, Rodda MS, Davidson J, Javid M, Stephens A, Slater AT, Cogan NOI, Forster JW, Kaur S, 2016. SNP-based linkage mapping for validation of QTLs for resistance to ascochyta blight in lentil. Front Plant Sci 7: 1604. https://doi.org/10.3389/fpls.2016.01604
  • Supek F, Bošnjak M, Škunca N, Šmuc T, 2011. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE 6: e21800. https://doi.org/10.1371/journal.pone.0021800
  • Tivoli B, Banniza S, 2007. Comparison of the epidemiology of ascochyta blights on grain legumes. Eur J Plant Pathol 119: 59-76. https://doi.org/10.1007/s10658-007-9117-9
  • Untergasser A, Nijveen H, Rao X, Bisseling T, Geurts R, Leunissen JAM, 2007. Primer3Plus, an enhanced web interface to Primer3. Nucleic Acids Res 35: W71-W74. https://doi.org/10.1093/nar/gkm306
  • Vaghefi N, Mustafa BM, Dulal N, Selby-Pham J, Taylor PWJ, Ford R, 2013. A novel pathogenesis-related protein (LcPR4a) from lentil, and its involvement in defence against Ascochyta lentis. Phytopathol Mediterr 52: 192-201.
  • Verma S, Gazara RK, Nizam S, Parween S, Chattopadhyay D, Verma PK, 2016. Draft genome sequencing and secretome analysis of fungal phytopathogen Ascochyta rabiei provides insight into the necrotrophic effector repertoire. Sci Rep 6: 24638. https://doi.org/10.1038/srep24638
  • Wang L, Feng Z, Wang X, Wang X, Zhang X, 2010. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics 26: 136-138. https://doi.org/10.1093/bioinformatics/btp612
  • Wei S, Winkelmann T, 2017. Transcriptomic profiling in leaves representing aboveground parts of apple replant disease affected Malus domestica 'M26' plants. Sci Hortic 222: 111-125. https://doi.org/10.1016/j.scienta.2017.05.012
  • Wei S, Bartsch M, Winkelmann T, 2017. Transcriptomic analysis of molecular responses in Malus domestica 'M26' roots affected by apple replant disease. Plant Mol Biol 94: 303-318. https://doi.org/10.1007/s11103-017-0608-6
  • Yakovlev IA, Lee Y, Rotter B, Olsen JE, Skrøppa T, Johnsen Ø, Fossdal CG, 2014. Temperature-dependent differential transcriptomes during formation of an epigenetic memory in Norway spruce embryogenesis. Tree Genet Genomes 10: 355. https://doi.org/10.1007/s11295-013-0691-z
  • Zajac BK, Amendt J, Horres R, Verhoff MA, Zehner R, 2015. De novo transcriptome analysis and highly sensitive digital gene expression profiling of Calliphora vicina (Diptera: Calliphoridae) pupae using MACE (Massive Analysis of cDNA Ends). Forensic Sci Int Genet 15: 137-146. https://doi.org/10.1016/j.fsigen.2014.11.013
  • Zawada AM, Rogacev KS, Müller S, Rotter B, Winter P, Fliser D, Heine GH, 2014. Massive analysis of cDNA ends (MACE) and miRNA expression profiling identifies proatherogenic pathways in chronic kidney disease. Epigenetics 9: 161-172. https://doi.org/10.4161/epi.26931